Technical Field
The present disclosure relates generally to autonomous vehicle navigation. Additionally, this disclosure relates to systems and methods for navigating a host vehicle based on detecting door openings, navigating a host vehicle based on detecting a target vehicle entering the host vehicle's lane, navigating a host vehicle based on detecting whether a road on which the host vehicle travels is a one-way road, and determining a predicted state of a parked vehicle.
Background Information
As technology continues to advance, the goal of a fully autonomous vehicle that is capable of navigating on roadways is on the horizon. Autonomous vehicles may need to take into account a variety of factors and make appropriate decisions based on those factors to safely and accurately reach an intended destination. For example, an autonomous vehicle may need to process and interpret visual information (e.g., information captured from a camera), information from radar or lidar, and may also use information obtained from other sources (e.g., from a GPS device, a speed sensor, an accelerometer, a suspension sensor, etc.). At the same time, in order to navigate to a destination, an autonomous vehicle may also need to identify its location within a particular roadway (e.g., a specific lane within a multi-lane road), navigate alongside other vehicles, avoid obstacles and pedestrians, observe traffic signals and signs, travel from one road to another road at appropriate intersections or interchanges, and respond to any other situation that occurs or develops during the vehicle's operation.
Autonomous vehicles must be able to react to changing circumstances with sufficient time to adjust a navigation path of the vehicle or to apply the brakes. Many traditional algorithms, such as those used in extant autonomous braking systems, do not have reaction times comparable to those of humans. Accordingly, such algorithms are often better suited for use as a backup to human drivers rather than use in a fully autonomous vehicle.
Moreover, characteristics of parked cars are often good indicators of characteristics of a road. For example, the direction of the parked cars may indicate whether the road is a one-way road, and the space between vehicles may indicate whether a pedestrian might emerge from between the vehicles. Existing autonomous vehicle algorithms, however, do not use such characteristics.
Finally, autonomous vehicle systems may use measurements to which human drivers do not have access. For example, autonomous vehicle systems may employ infrared cameras to assess the environment and make predictions. However, many traditional systems do not utilize a combination of measurements, such as visual and infrared cameras. Embodiments of the present disclosure may address one or more of the shortcomings of traditional systems discussed above.